weather

Seattle and New York daily weather from 2012–2015

Daily weather observations from Seattle and New York. Transformed from NOAA data using the script /scripts/weather.py. The categorical "weather" field is synthesized from multiple fields in the original dataset. Intended for instructional purposes.

CSV 2,922 rows 7 fields 121 KB 2 gallery examples 2 examples

Fields

FieldTypeDistributionSummaryMissing
location

City location of the weather observation (Seattle or New York)

string 2 distinct New York 1,461 · Seattle 1,461 Missing 0
date

Date of the weather observation

date Jan 1, 2012 – Dec 31, 2015 Missing 0
precipitation

Amount of precipitation in millimeters

number 0 – 118.9 · mean 2.95 Missing 0
temp_max

Maximum daily temperature in degrees Celsius

number -7.7 – 37.8 · mean 16.77 Missing 0
temp_min

Minimum daily temperature in degrees Celsius

number -16 – 26.7 · mean 8.61 Missing 0
wind

Wind speed in kilometers per hour

number 0.4 – 16.2 · mean 4.1 Missing 0
weather

Categorical weather type synthesized from original NOAA data fields. Categories include: drizzle, rain, snow, sun, and fog.

Values: drizzle, rain, snow, sun, fog

string 5 distinct sun 1,466 · rain 1,087 · fog 139 Missing 0

Profiled across all 2,922 rows.

Explore

Pick two fields. Scroll to zoom, drag to pan. Click the legend to isolate a location. Both fields have values in 2,922 of 2,922 rows.Pick two fields. Tap the legend to isolate a location. Both fields have values in 2,922 of 2,922 rows. Vega-Lite · input binding · scale binding · legend bindingVega-Lite · input binding · legend binding
Open This Chart in the Vega Editor

Preview

First 5 of 2,922 rows5 of 2,922 rows
locationdateprecipitationtemp_maxtemp_minwindweather
Seattle2012-01-010.012.85.04.7drizzle
Seattle2012-01-0210.910.62.84.5rain
Seattle2012-01-030.811.77.22.3rain
Seattle2012-01-0420.312.25.64.7rain
Seattle2012-01-051.38.92.86.1rain

Scroll sideways for all 7 fields.

Examples

Vega and Vega-Lite examples open in the Editor with this dataset loaded. Altair examples link to their Python source.

Provenance

Source
License
File
data/weather.csv · 121,417 bytes · View on GitHub